During the last three decades, Bayesian methods have developed greatly in the field of
epidemiology. Their main challenge focusses around computation, but the advent of Markov …

Spatial epidemiology is the description and analysis of geographic variations in disease with
respect to demographic, environmental, behavioral, socioeconomic, genetic, and infectious …

Background: The ongoing new coronavirus pneumonia (Corona Virus Disease 2019,
COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million …

Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed,
practically oriented & innovative presentation of the combination of Bayesian methodology …

Summary⇓ Information about the comparative magnitude of the burden from various
diseases and injuries is a critical input into building the evidence base for health policies …

Since the publication of the second edition, many new Bayesian tools and methods have
been developed for space-time data analysis, the predictive modeling of health outcomes …

The growth of biostatistics has been phenomenal in recent years and has been marked by
considerable technical innovation in both methodology and computational practicality. One …

Purpose The population and spatial characteristics of COVID-19 infections are poorly
understood, but there is increasing evidence that in addition to individual clinical factors …

With the advent of routine health data indexed at a fine geographical resolution, small area
disease mapping studies have become an established technique in geographical …

Although urban birth, upbringing, and living are associated with increased risk of
nonaffective psychotic disorders, few studies have used appropriate multilevel techniques …